In recent years, social media applications and panelist media consumption behavior applications have grown to produce relatively large quantities of data. Attempts to analyze the data from such applications is aided by decision trees, which include test nodes that analyze a particular variable from the data for a conditional result. For example, if an analyst attempts to obtain a subset of the data related to males less than twenty-five years old, then a first node may analyze the data with a male/female test node to test an inequality expression.
When the male/female test node evaluation results in “TRUE,” then the corresponding data points are associated with male panelists. Additionally, the resulting subset of data associated with the male panelists may further proceed to an age test node that tests data points for an inequality of “Less Than 25.” When the age test node results in a true statement, then that resulting subset of data points is associated with individuals (e.g., panelists) that are both male and less than twenty-five years old.